Optimal batch recursive data compression

A recursive linear optimal estimation method is presented which processes a batch of measured data at each estimation point. Due to this feature the new method serves as a data compression scheme. This scheme is an integrated one in the sense that the optimization is performed on a prefilter/estimat...

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Bibliographic Details
Published in:IEEE transactions on automatic control 1982-02, Vol.27 (1), p.169-176
Main Authors: Medan, Y., Bar-Itzhack, I.
Format: Article
Language:English
Subjects:
Covariance matrix
Data compression
Degradation
Filters
Gain measurement
Loss measurement
Noise measurement
Recursive estimation
State estimation
Time measurement
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Description
Summary:A recursive linear optimal estimation method is presented which processes a batch of measured data at each estimation point. Due to this feature the new method serves as a data compression scheme. This scheme is an integrated one in the sense that the optimization is performed on a prefilter/estimator combination. The method is derived and compared for accuracy performance and complexity with the Kalman filter. It is found that a considerable saving in computational effort, with a minimal degradation of accuracy, is achieved using this method. An example is presented and efficient algorithms to implement this method are developed.
ISSN:0018-9286
1558-2523
DOI:10.1109/TAC.1982.1102866